13 current, source-cited statistics on artificial intelligence in insurance: market size, adoption, claims automation, fraud detection, underwriting and ROI. Every figure links to its original source.
Insurance runs on data, claims, policies, risk and fraud signals, which makes it one of the clearest sectors for AI. This page collects the most-cited, verifiable statistics on AI in insurance from named sources, as a single reference to link to. It is a companion to our AI consulting for insurance page, which covers claims automation, fraud detection and underwriting AI and how we build them.
Every statistic is attributed inline to its source with a link, and figures reflect the wording of the original research. Market-size estimates vary between research firms; ranges are given where sources differ. Sources: Fortune Business Insights, Mordor Intelligence, Precedence Research, McKinsey, Earnix and Simplifai.
The AI in insurance market is projected to grow from about $13.45 billion in 2026 to $154.39 billion by 2034.
Source: Fortune Business InsightsThe AI in insurance market is forecast to reach $114.52 billion by 2031, registering a 34.20% CAGR, with North America holding 43.95% of the market in 2025.
Source: Mordor IntelligenceThe AI in insurance market is projected to increase from about $14.39 billion in 2026 to roughly $176.58 billion by 2035, a 32.21% CAGR.
Source: Precedence ResearchGenerative AI could unlock between $50 billion and $70 billion in additional insurance-industry revenue, concentrated in marketing, customer operations and software engineering.
Source: McKinsey, “The economic potential of generative AI”More than 78% of global insurance organizations reported active AI implementation in at least one business function during 2025.
Source: AI in Insurance Industry Statistics (Openkoda)76% of US insurance executives reported that their organization had implemented generative AI in one or more business functions, with stronger adoption among larger insurers by revenue.
Source: Earnix, 2026 Insurance Trends Report62% of insurance organizations are currently scaling AI initiatives across multiple functions, about 13% above the cross-industry average.
Source: AI in Insurance Industry Statistics (Openkoda)Automated claims systems reduced processing time by roughly 65% across major insurers.
Source: AI in Insurance Industry Statistics (Openkoda)AI-assisted underwriting improved policy-evaluation accuracy by about 42%.
Source: AI in Insurance Industry Statistics (Openkoda)Fewer than a quarter of insurers currently use AI for claims processing (23%), with only 18% for policy issuance and 15% for churn prediction; most of the value is still ahead.
Source: Simplifai / industry reporting52% of insurance organizations report revenue growth attributable to AI use, about 15% above the cross-industry average.
Source: AI in Insurance Industry Statistics (Openkoda)Roughly 99% of insurers in the US and Europe now have generative AI projects underway, adoption is effectively universal.
Source: Simplifai / industry reporting90% of insurance leaders recognise the need to reinvent how work gets done for AI, but only about 25% have taken meaningful action, the gap is execution, not intent.
Source: Industry reporting (ScienceSoft)The headline figures come from named market research. The AI in insurance market is projected to grow from about $13.45 billion in 2026 to $154.39 billion by 2034 (Fortune Business Insights); Mordor Intelligence puts it at $114.52 billion by 2031 at a 34.20% CAGR. On adoption, more than 78% of insurance organizations reported active AI use in at least one business function in 2025, and McKinsey estimates generative AI could unlock $50-70 billion in additional insurance-industry revenue. Every figure on this page is attributed inline to its source.
Very fast. By 2026 roughly 99% of insurers in the US and Europe had generative AI projects underway (Simplifai), 76% of US insurance executives reported implementing generative AI in at least one function (Earnix), and 62% of insurers are already scaling AI across multiple functions. About 13% above the cross-industry average.
The most-cited outcomes: 52% of insurers report revenue growth attributable to AI (about 15% above the cross-industry average), automated claims systems have cut processing time by roughly 65%, and AI-assisted underwriting has improved evaluation accuracy by about 42%. McKinsey estimates $50-70 billion in additional industry revenue, concentrated in marketing, customer operations and software engineering.
AI is landing hardest in claims processing, fraud detection, underwriting and customer service. But the runway is still large: fewer than a quarter of insurers currently use AI for claims processing (23%), only 18% for policy issuance and 15% for churn prediction; most of the value is still ahead.
Every statistic is drawn from a named, published source and linked inline, with the original wording preserved rather than rounded or altered. Sources include Fortune Business Insights, Mordor Intelligence, Precedence Research, McKinsey, Earnix and Simplifai. This page is maintained as a living reference and was last updated in August 2026.
The data keeps showing the same gap, execution, not intent. We build the production systems behind these outcomes: claims automation, fraud detection and underwriting AI, for insurers in weeks, not quarters.
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